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Compared to cast-in-situ construction, prefabricated construction reduces the generation of construction waste; however, construction waste cannot be entirely eliminated through prefabrication and can be generated at each stage of its life cycle. This paper generates a system dynamics model, comprising two causal-loop diagrams and one stock-flow diagram, to simulate the effectiveness of policies on decarbonizing prefabricated concrete building waste. The model can predict the annual and total construction waste, along with the associated carbon emissions, under different policy scenarios in China by 2030. This paper focuses on prefabricated concrete buildings in China, with specific attention to the wastage of concrete, bricks, mortar, and metal. In single-factor scenario simulations, increasing landfilling fee is the most effective policy for waste decarbonization, potentially reducing carbon emissions by 31%. Increasing prefabrication rate and enhancing regulation degree at the design phase of prefabrication can directly reduce prefabricated building waste generation, subsequently resulting in an 18% and 7% carbon emissions reduction. Multi-factor scenario simulations demonstrate that the simultaneous application of all four policies is most effective, achieving a 44% reduction in carbon emissions. This research establishes a theoretical framework for prefabricated concrete building waste management and provides the Chinese government with practical insights on optimizing policies for waste decarbonization in the dynamic landscape of prefabrication. • This paper develops the prefabricated building waste generation and disposal systems. • The model predicts the construction waste and associated carbon emissions by 2030. • Raising landfill fee is an effective policy for decarbonizing construction waste by 31.06%. • Prefabrication rate reaching 100% can reduce 18.04% of carbon emissions from waste. • Applying all policies is most effective, achieving a 44.34% carbon emissions reduction. [ABSTRACT FROM AUTHOR]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether emission reduction commitments contribute to carbon risk premium. Therefore, based on a sample of Chinese listed companies that publicly disclosed questionnaires in the CDP from 2009 to 2021, this paper empirically examines the relationship between emission reduction commitments and carbon risk premium and their formation mechanism. The results show that emission reduction commitments can effectively hedge the carbon risk premium, which pass several robustness tests. Specifically, the more comprehensive and ambitious the commitment is, the greater the suppression of the carbon risk premium. The mechanism test shows that disclosing emission reduction commitment information can reduce carbon risk by improving investor confidence and attracting political resources. Differences in enterprise emission levels, regional environmental regulation intensity and green financial development result in different risk-hedging effects of emission reduction commitments. Moreover, the greater the substantial pressure from stakeholders, the greater the tendency for firms to set up emission reduction commitments. Finally, the heterogeneity analysis reveals that confidence level of commitments has a significant impact on risk premium. Specifically, enterprises with SBTi validation, higher CDP ratings and higher target completion are more helpful in curbing carbon risk premium. Our findings contribute to corporate commitment to climate change and complement the carbon risk premium hypothesis. [Display omitted] The possible highlights of this study are as follows. • With the help of forward-looking information on emission reduction commitments, we re-examine the conclusion of the carbon risk premium and find that emission reduction commitments can effectively hedge the risk premium, enriching and developing the carbon risk premium hypothesis • This paper brings commitment levels and carbon emission levels into a unified analytical framework to study the correspondence between emission reduction commitments made under pressure to reduce emissions and the carbon risk premium, providing micro evidence for solving the mystery of the carbon risk premium. • Measure emission reduction commitment indicators from various angles, making the data on emission reduction commitments more objective and scientific. [ABSTRACT FROM AUTHOR]

Cities have emerged as critical and challenging places for promoting the green and low-carbon transformation of the economy and society in the context of the "dual carbon" targets. Meanwhile, fiscal policy is also an indispensable component of the public policy framework supporting the green and low-carbon transformation. This paper uses the pilot project of "Comprehensive Demonstration Cities for Energy Conservation and Emission Reduction Fiscal Policies" ("ECER-CD" policy) implemented in China since 2011 as a quasi-natural experiment. This research theoretically analyzes and empirically tests the energy conservation and emission reduction effects of fiscal policies supporting green and low-carbon transformation utilizing methodologies such as time-varying DID and multiple periods and multiple groups of DID. The study finds that the pilot cities effectively reverse the behavioural bias of local governments and promote energy conservation and emission reduction efforts. This conclusion holds after undergoing robustness tests such as parallel trend analysis and heterogeneity treatment effects. The effectiveness of the pilot policy is attributed to the upgrade of industrial structure, improvement of energy efficiency, and the effects of green technology innovation. However, cities' geographic location and resource dependency can interfere with the effective implementation of policies. This paper also further explores the environmental dividends and economic consequences of the policy and finds that the pilot cities have certain environmental dividends and do not significantly restrain economic and social development. This study broadens the research perspective on fiscal policies in energy conservation and emission reduction and clarifies the pathways through which fiscal policies promoting green, low-carbon transformation drive energy conservation and emission reduction in cities. Moreover, it also improves the use of the Difference-in-Differences method in evaluating policy effects in scenarios such as the overlapping implementation of pilot policies and policy withdrawal. Finally, this paper proposes policy recommendations to provide more empirical evidence for China to accelerate the green and low-carbon transformation of the economy and society. [ABSTRACT FROM AUTHOR]

Existing studies on emission accounting in global value chains (GVCs) have not focused on the relational nature of GVC activities manifested as the interaction of intermediate goods between enterprises. This paper proposes a relational GVC emissions accounting framework based on an inter-country input-output (ICIO) model distinguishing between domestic-owned enterprises (DOEs) and foreign-invested enterprises (FIEs), which is classified as trade-based, investment-based and hybrid-based emissions. Using AMNE-ICIO tables from 2005 to 2016, this paper traces emissions and carbon intensity in relational GVC activities at the global, economic, and industry levels. We find the following: (1) Investment-based emissions accounted for about 94.15% of the increase in relational GVC emissions, of which more than half comes from the interactive activities between DOEs and FIEs. (2) For the United States, high-income economies, and high-tech manufacturing, investment-based emissions were higher than trade-based emissions, and the reverse was true for upper-middle and lower-middle income economies and China. (3) Although relational GVC carbon intensity was high, the trend of decline was significant. (4) Compared to trade activities, investment-based activities were less carbon intensity in China and upper-middle income economies due to the interaction of production between FIEs and DOEs. The findings add new insights into the coordination of global emissions reductions and the allocation of emissions responsibility. • Emphasize the interdependence between enterprises in cross-border production. • Combine GVC linkages with carbon emissions and carbon intensity. • Investment-based emissions are the main factor of relational GVC emissions growth. • The carbon intensity of relational GVC decreased significantly. • Developing countries can access green spillover through investment-based GVC links. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive system for assessing contaminant emissions, including the dominant contaminant reduction effects, recessive contaminant reduction effects, and contaminant reduction efficiency indexes. The system is used to evaluate the linkage changes in contaminant emissions reduction across different sectors, the ease of regulation, and the returns on emissions reduction efforts. The study's results demonstrate that firstly, COVID-19 initially reduced contaminant emissions across almost all sectors, although this effect waned over time. Secondly, applying conventional regulatory measures to sectors with high reductions in contaminant emissions may not yield the expected results. Thirdly, while some sectors may be more difficult to regulate, they may offer a higher return on investment in terms of emissions reduction. Based on the above results, the paper advocates for timely measures to consolidate environmental gains, prevent rebounding of contaminant emissions, prioritize supervision and management of easily regulated sectors, prioritize upgrading of cleaner production in sectors with high reduction efficiency indices, and increase investment in environmental technology. • Created a new comprehensive system for assessing contaminant emission changes. • Quantified the unique linkage changes of contaminant emissions during COVID-19. • Developed new models to reveal contaminants' regulatory difficulty and return. • The innovative reduction effects of four key contaminant indicators were measured. • Applied WHEM firstly in research across multiple areas of contaminant emissions. [ABSTRACT FROM AUTHOR]

China's industry is facing a carbon lock-in (CLI) dilemma. Based on the complexity and dynamics of CLI, exploring diversified unlocking paths is an important way to achieve emission reduction goals. This paper innovatively applies system dynamics (SD) to the study of CLI prediction and unlocking path, and systematically constructs an industrial CLI SD model, trying to break the positive feedback mechanism of CLI through multiple causality and feedback chains. This paper simulates and predicts the changing trend of the CLI level of China's industry and 8 major subsectors from 2020 to 2050. At the same time, the random forest algorithm is used to select the regulatory variables of policy analysis. Compared with the previous research methods, the accuracy and objectivity of the selection of regulatory variables are improved, so as to test the effectiveness of the unlocking path under each scenario. The results show that (1) the whole industry faces a serious CLI problem and is still in a deep lock-in state. From the perspective of subsectors, the light, electromechanical, and textile industries have achieved unlocking; the oil and extractive industries are in a moderately lock-in state; the chemical, steel, and power industries are in a deep lock-in state; and the CLI situation is serious. (2) The results of the random forest algorithm show that R&D investment, the proportion of fixed asset investments in the energy industry, car sales, energy structure, and carbon emission industry structure are the most significant factors affecting CLI in each subsystem. (3) Compared with the existing economic development model, the technological, institutional, social, and comprehensive unlocking scenarios can all enable industry to achieve carbon peak and carbon unlocking in advance. However, the effect of each scenario is as follows: comprehensive unlocking scenario > technological unlocking scenario > institutional unlocking scenario > social unlocking scenario. (4) The unlocking times of the oil, chemical, steel, and power industries are relatively late in each scenario. To realize carbon unlocking in industry, these four areas should be focused on in the future. This study helps policymakers formulate reasonable policies to accelerate industrial carbon unlocking and promote the implementation of the "dual carbon" strategy. • The whole industry faces a serious carbon lock-in problem. • The technological, institutional, social and comprehensive unlocking scenarios can all achieve carbon unlocking in advance. • The comprehensive unlocking scenario has the best effect, and the social unlocking scenario has the worst effect. • The oil, chemical, steel and power industries should be focused on in the future. [ABSTRACT FROM AUTHOR]

Green finance is a financial innovation that directs capital allocation towards green industries. How will this affect regional carbon emissions? Based on the data on green finance and carbon emissions of 30 provinces in China from 2008 to 2019, this paper employs a multivariate linear regression model and a spatial econometric model to empirically study the impact of green finance on carbon emissions. The results find that (1) green finance significantly reduces provincial carbon emissions, specifically through promoting a cleaner energy structure and an advanced industrial structure, as well as improving the quality of green innovation. (2) Heterogeneity exists between regions. In eastern regions and areas characterized by high levels of marketization and minimal fiscal pressure, the role of green finance in promoting provincial carbon emission reduction is more pronounced. (3) Spatial econometric analysis found that green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. Specifically, the flow of green resources and green ideas between provinces facilitates the formation of regional radiation, while green competition generates a siphon effect on neighboring regions. These findings provide some meaningful policy implications to achieve China's dual-carbon goal by promoting green finance. • Green finance has significantly reduced China's provincial carbon emissions. • The upgrading of energy structure and industrial structure is a positive channel to reduce carbon emissions. • Green innovation strengthens the carbon reduction effect of green finance, but reveals the potential "greenwashing". • Green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. • Policymakers should develop flexible, dynamic and coordinated green finance development policies. [ABSTRACT FROM AUTHOR]

Abstract The purpose of this paper is to evaluate greenhouse gas (GHG) emissions of a Chinese highway tunnel in the life cycle. Life cycle assessment (LCA) method is adopted in the paper. Based on rock mass classification and pavement categories, five different functional units have been proposed for the first time. The system boundaries, processes and assumptions are defined. The study results indicate: 1) the GHG emissions of a double-track four-lane Chinese highway tunnel in 100 years can be up to 375.5 thousand tons of CO 2 eq. Cement and electricity contribute to more than 80% of the total emissions in all functional units. 2) The construction stage, operation stage and maintenance stage emit 30.89%, 56.12% and 12.99% of the total GHG respectively. During the construction stage, casting and lining, rock support and road work are the top three GHG emission processes. 3) Rock conditions are discovered to be an important factor of affecting GHG emissions in tunnels. The GHG emissions of the 1-m Chinese highway tunnel are between 82 t to 113 t CO 2 eq. With the increase of rock mass grades, GHG emissions rapidly rise if the pavement design stays the same. The emission differences among the functional units are mainly from materials. 4) Asphalt pavements tend to generate more GHG emissions than concrete pavement due to the more frequent replacements of asphalt pavements. This paper investigates the influences of rock conditions and pavement types on the GHG emissions of Chinese tunnels in the life cycle, which can provide a scientific reference for policy making of the Chinese government. [ABSTRACT FROM AUTHOR]

Thanks to many government incentives, China has provided, at relatively low prices, a number of solar PV products to the world and enhanced domestic solar PV power. While China's growing solar PV industry has brought about both domestic and international environmental benefits, the provision of heavy subsidies has motivated the discussion of social and economic benefits and costs of this technology. Using the LCA approach, this paper performs an in-depth analysis on the environmental benefits and costs of this industry for the period of 2011–2016. Differing from existing literature, this paper broadens system boundaries to cover 11 stages of the solar PV industry life cycle, taking module sources and market directions of PV system into consideration, and quantifies the costs of environmental emissions of the industry by shadow pricing. The key finding of this study is that during 2011–2016 the total environment benefit was smaller than the total cost of China's solar PV industry. Meanwhile, coinciding with the rise of the domestic solar PV market, the resulting net environmental benefits have witnessed dramatic yearly growth. Policy implications and conclusions from findings are provided at the end of this paper. [ABSTRACT FROM AUTHOR]

Given the urgency of the transition to renewable energy, this study examines the challenges and opportunities associated with the electrification of heavy-duty vehicles, particularly new energy construction dump trucks, in China. Through a combination of policy analysis and empirical research, it investigates drivers' purchase intentions towards these alternative energy vehicles in a designated study area. The findings reveal that while policies aimed at encouraging adoption are in place, drivers' purchase intentions remain low due to factors such as high costs, technical concerns, inadequate infrastructure, and satisfaction with existing trucks. Specifically, the study identifies key technical challenges, including battery performance and range limitations, and advocates for a shift in policy support towards product development to address these issues. Overall, the paper highlights the need for a comprehensive approach that combines policy incentives with technological advancements to promote the widespread adoption of new energy construction dump trucks in China and achieve sustainability and carbon neutrality goals in the transportation sector. [ABSTRACT FROM AUTHOR]

In order to probe collaborative environmental governance (CEG) in China's "1 + N" policy framework for carbon peak and carbon neutrality, this paper applies the Actor-network theory (ANT) as an analytical framework to explore carbon reduction policy coordination. We then model ANT's relations with an evolutionary game theory (EGT) model to examine the evolutionarily stable strategies in CO 2 emission reduction by various actors including the central government, local governments, commercial banks, and polluting enterprises. Our objective is to examine policy coordination as the key enabler for governing success via an ANT-based mechanism design in China's institutional context. Combining the strength of ANT with a four-party EGT model, we investigate how to improve policy coordination to mobilize the actor-network for promoting CEG. Simulations are conducted to examine the effectiveness of policy coordination involving multiple policy instruments for controlling carbon emissions. The central government fulfills leadership in translating the interests of other actors and shaping the desired collaborative network. Without proper coordination, environmental policies may counteract each other. Government transfers and subsidies have direct impacts, but in the long run enhanced competitiveness and profitability of enterprises represent the intrinsic key to CEG success. From a methodology perspective, policy simulation in an EGT framework represents a novel addition to the research toolbox that expands ANT. [ABSTRACT FROM AUTHOR]

Cities are the main source and gathering place of carbon emissions. Therefore, it is an effective way to reach peak CO 2 emissions before 2030 to make carbon emission prediction and implement differentiated carbon emission reduction schemes according to local conditions at the urban level. Taking Shandong Province as an example, this paper comprehensively explored the impact of 16 socio-economic factors on carbon emissions of different cities through the extended STIRPAT model. In order to reduce the uncertainty of the research results and achieve "one city, one policy", firstly, the influencing factors of carbon emissions in different cities were screened through ridge regression equation, which were used as specific parameters of different cities in the scenario setting. Secondly, based on the actual development of different cities, this paper obtained the scenario combination scheme by freely combining different influencing factors to predict the peak time and peak value of carbon emissions. Based on the above measures, it could not only reflect the heterogeneous development of cities, but also ensure that the research results are close to the actual development of cities. The results show that 16 cities in Shandong Province show differential peak attainment. Among them, 8 cities have the best peak year around 2025, 5 cities have the best peak year around 2028, and 2 cities can achieve the peak before 2030. A comprehensive analysis of the timing and peaking of carbon emissions suggests that the best overall peaking year for Shandong Province could be 2028. In addition, according to the different influencing factors of carbon emission peak in each city, a set of carbon emission reduction scenarios with urban differentiation reaching the peak is proposed. This could provide a more comprehensive path choice direction for local governments to formulate carbon emission reduction action plans. Furthermore, this paper could be used as a reference for other provinces in China or other national regions to explore urban differentiated carbon peaking and to formulate operable carbon peaking solutions. [Display omitted] [ABSTRACT FROM AUTHOR]

Digital technologies are a key driver of carbon peaking and carbon neutrality. However, as the physical foundation supporting digital technology, how digital infrastructure affects carbon emissions is unclear. Based on the panel data from 2008 to 2019, this paper examines the impact of the Broadband China Policy on carbon emissions by adopting a multi-period difference-in-differences (DID) method. The empirical findings indicate that, first, digital infrastructure development plays a significant role in reducing carbon emissions in China. Second, the Broadband China Policy significantly reduces carbon emissions especially in China's low-carbon emission regions, high-level digitization regions, and non-resource-cursed regions. Third, the implementation of the Broadband China Policy facilitates carbon emissions reduction through the promotion of green technology progress, optimization of industrial structures, green transformation of residents' lifestyles, and electrification of energy mix. Finally, the Broadband China Policy has a positive spatial spillover effect on the carbon intensity in the surrounding regions of pilot cities, but it has no significant effect on the total carbon emissions and per capita carbon emissions in the surrounding regions. The results provide important insights for digital infrastructure construction to achieve a win-win situation for economic development and emission reduction. • It explores the impact of Broadband China Policy on carbon emissions reduction. • Digital infrastructure development has positive impact on reducing carbon emissions. • The reduction effect is heterogeneous in regions with different characteristics. • Carbon emissions can be reduced at both industrial and individual levels. [ABSTRACT FROM AUTHOR]

The significant carbon emissions generated by China's sludge treatment industry cannot be ignored. However, with only a few recent well-executed studies on carbon emission reduction in the sludge treatment field, the literature awaits a more comprehensive assessment and prediction whether the sludge treatment industry can achieve the dual-carbon target. This article aims to fill this gap, holistically examining the carbon emission reduction potential in the industry. Using the moving average method and IPCC method, the projected carbon emission value of sludge treatment in China from 2021 to 2030 indicates a total net carbon emission of 0.3 million tons by 2030. This suggests that the sludge treatment industry is on track to meet the carbon peak target, leaving surplus carbon quotas or credits available to assist other industries for carbon emissions reductions. The study also finds that only incineration and composting demonstrate the potential to be able to partially offset carbon emissions through resource utilization in certain stages or processes. Therefore, the current sludge treatment methods do not yield comprehensive emission reduction effects and cannot provide sufficient contribution to China's dual carbon goals. To address this issue, the paper explores a new scheme that focuses on improving the sludge treatment process. The scheme comparative analysis reveals that, even with all sludge treatment methods optimized, the total net carbon emissions of the industry could only be reduced to 0.058 million tons. This reduction falls short of significantly mitigating carbon emissions to achieve the carbon neutrality goal. Therefore, industries unable to achieve substantial net carbon reduction may need to explore alternative measures, such as carbon sinks, to ultimately attain carbon neutrality. [ABSTRACT FROM AUTHOR]

China has implemented the coal-to-clean-energy shift policy in rural areas of northern China to improve air quality, optimize energy structure and reduce greenhouse gas emissions, resulting in a significant increase in natural gas and electricity consumption. The policies shifts can reduce CO 2 emissions, but methane emissions from switching processes may contribute to short-term climate impacts. The climate impact during the policy transition is still unclear. Thus, this paper developed a lifecycle greenhouse gas (GHG) emissions framework for coal-to-clean-energy policies in rural northern China. The GHG emissions for heating and cooking, the two most energy intensive activities, were calculated. Four scenarios were designed based on energy types and equipment. Uncertainties in estimating lifecycle GHG emissions under different scenarios were analyzed. The technology warming potential values were calculated for the conversion of scenarios. Besides, the environmental benefits of natural gas versus electricity under emission reduction targets were compared. According to our findings, the total GHG emissions reduction of coal-to-clean-energy shift policies in rural northern China under global warming potential on a 100-year scale (GWP 100) is 1.83 million metric ton CO 2 equivalent (MMT CO 2 eq) in 2018. Since the climate benefits of policy shifts are driven by chosen technical routes, replacing coal with natural gas should be prioritized; heating with natural gas boilers can maximize GHG emissions reduction and climate benefits. By 2038, the climate benefits of electricity will be far superior to those of natural gas, based on emission reduction targets and electrical mix. There are numerous opportunities to reduce GHG emissions in China's energy sector, and there is a need for the energy industry to obtain better emissions data as well as to increase efforts to reduce GHG emissions. [Display omitted] • The coal-to-clean-energy policy in rural areas has a positive climate benefit. • Priority should be given to replacing coal with natural gas in policy execution. • Heating and cooking with electricity will maximize climate benefits from 2038. • Climate impact caused by CH 4 emission during the energy lifecycle can't be ignored. [ABSTRACT FROM AUTHOR]

The industrial sector has significantly contributed to global climate change and urban air pollution while driving economic development. This paper takes the synergistic CO2 and SO2 emission reduction in China's industrial sector as an entry point quantifies the synergistic CO2 and SO2 emission reduction effect using the Kaya extension model and analyzes the synergistic emission reduction expansion mechanism in depth. It is found that the synergistic effect of CO2 and SO2 in the industrial sector is prevalent in most provinces in China. Every 10,000 tons of CO2 emission reduction leads to 1600 tons of SO2 emission reduction. Regional heterogeneity also clarifies that there are differences in synergistic emission reduction among different provinces, with most regions having a significant positive effect of synergistic emission reduction, while a small number of regions have an inverse effect, and direct SO2 reduction measures should be considered separately. The interaction effect analysis found that energy efficiency improvement in the industrial sector is the critical path to synergistic effect enhancement. At the same time, R&D expenditure and fixed asset investment have a weak effect on synergistic emission reduction. The interaction of the three factors can synergize the emission reduction effect by more than twice. The study's findings can be used as a reference for China's industrial sector to achieve the goal of reducing pollution and carbon emissions and for the practice of regional synergistic emission reduction, as well as for the formulation of international synergistic emission reduction policies. [ABSTRACT FROM AUTHOR]

Towards the target of carbon neutrality, the need for deep decarbonization in iron and steel industry is increasingly recognized. Existing studies rarely mention the effects of collaboration with its source industries for carbon emission reduction in ISI. Furthermore, the fundamental laws of CO 2 emission reduction capacity with cost change of source substitutions for various steel production routes under market economics are unclear. To avoid the blind substitution of clean sources for meeting the urgent requirements for decarbonization in China's steel industry, which may result in increased carbon emissions and uneconomical carbon reduction from a lifecycle perspective. This paper integrates the production and utilization processes of source resources into the steel production process, establishes coupling models of carbon and value flows for four main types of steel production routes, and aims to quantitatively analyze the specific CO 2 emission reduction potential and costs. Three economic market development scenarios from 2021 to 2060 are set, and the marginal carbon prices of various source substitutions are determined. Subsequently, decarbonization pathways with the goal of minimizing production costs are developed. Finally. The future resource demand and the carbon emission reduction contributions of source industries collaborated are predicted. The results show that (1) about 81.7–89.9 % of CO 2 emissions could be reduced in the scenarios; (2) the demands of electric power and hydrogen energy will reach 54.48–511.90 BkWh and 7.47–10.31 Gt in 2060, respectively; and (3) collaboration with source industries could make 18.3–18.3% of CO 2 emission reduction contributions. All in all, this study could provide scientific support for the low-carbon transformation of China's steel industry. • Carbon and value flows of BF-BOF, Scrap-EAF, DRI-EAF, MOE-EAF routes are analyzed. • CO 2 emission reduction potential with marginal carbon price is determined. • Decarbonization paths during 2021–2060 for China's steel industry are developed. • Quantify the contribution of collaborative carbon reduction with source industries. [ABSTRACT FROM AUTHOR]

The vigorous development of the digital economy (DIEC) offers a substantial potential for China and global economies to realize the goal of "double carbon". This study attempts to analyze the heterogeneous effect of DIEC on carbon emission reduction (CERE), in order to extend a valuable reference for effectively achieving the dual-carbon goal. Accordingly, the effect of DIEC on carbon emission scale (CESC) and carbon emission intensity (CEIN) are examined in this paper by using dual fixed effect model and intermediate effect model, respectively. The study findings show that, at first, DIEC significantly supports the CERE while significantly constraining the uplift in CESC and CEIN. Simultaneously, the CERE effect of DIEC contains digital economy dimensional heterogeneity, industry heterogeneity, production and life heterogeneity, and urban-rural heterogeneity. Finally, the DIEC boosts the technological innovation (TEIN) and residents' income (REIN) levels, in order to heighten the CERE. Further, improving invention technology innovation and TEIN is more conducive to catalyzing the reduction of carbon emission in the whole society and the production field. Conversely, the improvement of non-invention technology innovation and rural- and urban residents' income impedes CERE in the field of life. Thus, the implications of this study are of vital significance for China and the rest of the world to foster CERE and achieve the "dual carbon" goal through DIEC development. [ABSTRACT FROM AUTHOR]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

Carbon emission trading, a market-incentive environmental regulation, plays a critical role in leading China towards the carbon peaking and carbon neutrality. To improve the national carbon emission trading in China, we analyze the effects of the policy in pilot provinces and pilot A-share listed firms from 2008 to 2016. Particularly, to explore the pilot policy's environmental and financial impacts, this paper applies a difference-in-difference method. After the robustness check, the results confirm the carbon emission trading pilot's significantly positive impact at both firm- and province-level regarding carbon emission reduction. Meanwhile, corporate innovation seems to partially mediate the relationship between the policy and corporate carbon emission reduction. Plus, the policy promotes firms' market-based financial performance but such impact on accounting-based financial performance is insignificant. Ultimately, the operational mechanism of the policy is proved to be effective. In this paper, industry- and firm-level carbon emissions databases are established via environmental extended input-output table, which fill the research gap of China's firm-level carbon emissions. To ensure the reliability of results, the list of covered firms is sorted out manually in accordance with the disclosed data of seven carbon trading markets. Our results are meaningful for avoid productivity reduction and mechanism re-design in the context of the national carbon emission trading launched in 2021. Specifically, encouraging firms to further improve their productivity and competitiveness by innovation could eventually achieve a win-win situation between economic performance and environmental merits in the long run. [ABSTRACT FROM AUTHOR]

Energy and resource consumption has been expanding quickly with the rapid growth of Asian cities, which has resulted in increased greenhouse gas emission and waste generation. The promotion of low-carbon industries is an urgent global issue that extends to Asia as well. To reduce carbon dioxide emission substantially, industries must not only introduce energy-saving technologies but also use low-carbon raw materials and fuel, such as recyclable wastes and carbon-neutral biomass. This paper presents the concept of a “hybrid industry,” that is, an industry whose processes utilize not only fossil resources but also recycled and renewable resources as much as possible. This study examines the feasibility of hybrid industries through the promotion of urban symbiosis in cities in three Asian countries with different circumstances: Kawasaki in Japan, Ulsan in Korea, and Shenyang in China. Asian cities are in the midst of shifting from dumping wastes to incineration. However, in view of the carbon reduction effect of recycling as well as the cost for recycling and appropriate treatment of wastes, the potential of hybrid industries that use combustible municipal wastes as input should be considered. In this study, the potential for carbon dioxide reduction as well as the costs of promoting hybrid industries are evaluated. The results highlight that promoting hybrid industries generates significant environmental benefits for the three cities, and there are important factors that affect the cost-effectiveness of hybrid industries, including the spatial density of waste generation, composition of wastes, relative labor cost for collection and pre-treatment of wastes compared with construction cost of an incinerator and avoided costs through product and fossil resource substitution, and the willingness of citizens to separate wastes. Finally, key drivers for promoting hybrid industries through urban symbiosis in Asian cities are discussed. [ABSTRACT FROM AUTHOR]

The majority of the total greenhouse gas (GHG) emissions in China are energy-related. Thus, full understanding of energy-related GHG emissions is crucial for local governments to establish a baseline for tracking emission trends and developing mitigation strategies. In this paper, we present a survey-based GHG emission accounting method for sectoral energy consumption and apply it in Xiaolan, a typical town of Zhongshan. The method combines scope and sectoral analyses on the basis of local statistical approach, and pays more attention to data collection process. Scenarios of core findings in the study are list as below: (1) The energy-related GHG emissions of Xiaolan in 2010 was 2,072,444 tons of carbon dioxide equivalents (CO 2 e). Of this, 31.83% was Scope 1 emissions (direct emissions) and 68.17% was Scope 2 emissions (indirect emissions); (2) Emissions from “manufacturing”, “residents”, and “power, gas & water production and supply” made up 90.27%, among which, “manufacturing” represents the biggest emitting sector as 69.09%; (3) In 2010, the per capita GHG emissions was lower than that in most of the other Chinese cities, but higher than several Asian cities including Amman and Tokyo. Some strategic approaches to reduce GHG emissions were proposed: (1) save energy and improve energy efficiency; (2) optimize energy structure and develop low-carbon energy; (3) update manufacturing structure; (4) improve GHG emission management for the resident sector. Finally, we identified a number of key research issues to advance the town level GHG emission method for future research needs. This paper provides a useful method to understand and profile GHG emissions for towns. [ABSTRACT FROM AUTHOR]

Promoting low-carbon development in the iron and steel industry (ISI) is essential for China to achieve the carbon neutrality targets. This paper separately adopts the Logarithmic Mean Divisia Index (LMDI) technique and the Mean Impact Value (MIV) method to analyze the impact of driving factors on the CO 2 emissions of ISI in the historical and future dimensions. Furthermore, this paper establishes the extreme learning machine model optimized by the bat algorithm (BA-BP) to explore the carbon emission reduction pathways of ISI in the business-as-usual (BAU) scenario, the low-speed, medium-speed and high-speed development scenarios considering the constraints of carbon neutrality targets. The results reveal that: (1) Production capacity and energy efficiency are important drivers of CO 2 emissions in ISI; (2) The emission reduction situation is not optimistic under the BAU scenario, and it is difficult to accomplish the carbon neutrality goals by 2060; (3) Under the most ideal emission reduction pathway (corresponding to the high-speed development scenario), ISI will reach its peak in 2022 with the peak value of 2143.42 MtCO 2. Compared to the peak year, the CO 2 emissions will be reduced by 654.69 MtCO 2 and 1558.61 MtCO 2 in 2030 and 2050, respectively. Moreover, the achievement of short-term and long-term emission reduction targets depends on production capacity decline and technological progress, respectively. The optimal emission reduction pathway provides a reference for ISI to formulate periodic emission reduction targets. • The improved extreme learning machine is employed to predict the carbon emissions. • The emission reduction pathways are explored under the carbon neutrality target. • Controlling production capacity is a crucial reduction strategy. • The energy rebound effect is supposed to be weakened. • The application of advanced technologies will greatly promote emission reduction. [ABSTRACT FROM AUTHOR]

The increasing pressures of global warming, population growth and epidemic occurrence are causing challenges in meeting the growing requirements for water, energy and food. In particular, the contradiction between the supply and demand for water, food, and energy is exacerbated by inefficient resource utilization and carbon emission increase. Incorporation of the interlinked aspects of water, energy, food and carbon emissions from agricultural systems into one water-food-energy-carbon nexus facilitates integrated resource management. Biochar application to farmland is a potential strategy for carbon management and agricultural productivity improvement. The integration of biochar systems and the water-food-energy-carbon nexus is an efficient and coordinated alternative method for sustainable agricultural management and a crucial strategy for addressing water, energy and food security issues. Accordingly, this paper proposes an approach for the synergistic regulation of water, land, energy, and carbon emissions in a circular agricultural system by balancing water supply and demand, land allocation, electricity consumption, and economic upgrading principles. A two-stage circular agriculture framework is constructed, with biochar and electricity generated from agricultural residues at the first stage and employed at the second stage. Economic-environmental-energy harmonization is considered in the methodology, and the agrotechnical potential of biochar is quantified via crop yield increase and greenhouse gas emission reduction functions. This approach can assist decision makers in providing the best policy options given certain agricultural resources to achieve the maximum economic performance of the system while minimizing environmental side effects. In this paper, the model framework is applied to the Sanjiang Plain in northeastern China to verify the feasibility of the approach. The results indicate that the external electricity demand is reduced by 87.8% due to the generation of biofuels. Cropland greenhouse gas emissions are reduced by 34.09%–67.06% via the application of biochar. This study proposes an optimization method with important implications for the improvement of regional cropland management techniques and development of sustainable circular agriculture. This methodology can be extended to other agriculture-centered regions with limited resources and environmental problems. • Carbon cycle is integrated in agricultural water-food-energy-carbon (AWFEC) nexus. • An AWFEC nexus based model is developed for agricultural resources recycling. • Biochar and electricity are optimized sustainably for circular agriculture. • Analysis of resources recycling on economic-environmental balance is performed. [ABSTRACT FROM AUTHOR]

The digital economy is of great significant for carbon emission reduction. To estimate the impact on carbon emissions of digital economy, this paper conducts nonlinear analysis with the combination of spatial DURBIN model (SDM) and panel threshold model (PTM). Moreover, this paper decomposes the carbon emissions reduction effect into direct part and spatial spillover part, further analyzes the action mechanism from the perspective of technology progress, energy use and industrial structure. The empirical results indicate that the digital economy and carbon emissions have inverted U-shaped relationship. Similarly, the spatial spillover effect of digital economy on carbon emissions is also inverted-U shape. The digital economy increases first and then reduces the carbon emissions. The robustness tests and endogenous analysis both support above conclusions. Compared with the indirect effect, the direct effect of digital economy on carbon emissions is significantly greater. Moreover, the long-term effect of digital economy on carbon emissions is greater than the short-term effect. The impact of digital economy on carbon emissions exists regional heterogeneity. Different from the eastern and central regions, the digital economy in western region promotes carbon emissions monotonically. The impact of digital economy on carbon emissions faces significant resource endowment thresholds, urban scale thresholds and innovative capability thresholds. The increase of energy use and non-green technology progress are the main paths to influence local carbon emissions in short term, while the green technology progress and industrial structure upgrade become dominant paths in long term. The active demonstration of industrial structure upgrade and technology spillovers drive the spillover effect of digital economy on carbon emissions in long term. This paper suggests that, the realization of carbon peak and carbon neutral needs to strengthen the digital economy and promote the regional cooperation in environmental governance. The green integration of digital economy and traditional industries is of great significant for carbon emission reduction. [ABSTRACT FROM AUTHOR]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether green finance contributes to carbon emission reduction. Therefore, based on the panel data of 30 provinces in China from 2005 to 2020, this paper empirically examines the impact of green finance on carbon emissions and its mechanism using the FE model, GMM model, DID, and the mediating effect model. Results find that green finance can significantly promote carbon emissions reduction, and this promotion remains still after robustness tests. The heterogeneity analysis shows that green finance's carbon emission reduction effect is more significant in developed and western regions. Moreover, the results of policy intervention effects confirm that green finance reform and innovation pilot zones (GFRIs) for carbon emission reduction are more pronounced than in other regions. Finally, the mediating effects reveal that industrial structure and green innovation are the core transmission channels through which green finance influences carbon emission reduction. These findings offer meaningful implications for formulating reasonable carbon emission reduction plans and determining the future development direction of green finance. [ABSTRACT FROM AUTHOR]

This paper presents an energy-sharing market coupled with carbon emission trading to quantify peer-to-peer energy-sharing markets' economic and environmental influences. We establish a bi-level peer-to-peer energy sharing market considering the interaction between energy prosumers and the system operator. An interaction algorithm and generalized Nash game are thus applied in this work. With the simulation results, we find that the daily disutility of provincial systems is reduced by about 7 ¥ when time-of-use electricity rates are applied. This pricing strategy can encourage prosumers to participate in energy-sharing transactions. The subsidies of electricity rates, carbon prices, and renewable energy investments can improve the social welfare of the whole system. Considering the development of power generation technology and emission reduction targets, the change of optimization parameters in the next 30 years is analyzed in the example. It can be concluded that the total CO2 emission in 2050 will be reduced to almost half of that in 2020 in the energy-sharing markets. The subsidy of renewable energy generation and stricter CO2 emission constraints may accelerate the reduction of carbon emissions. [Display omitted] • It is the first time to assess the environmental effect of peer-to-peer energy trading with actual data. • We analyze the peer-to-peer energy trading impacts on the carbon emission amount in China. • We compare the market participants' revenue and CO2 emission considering the different scenarios. • We develop a bi-level coupled emission right trading market to verify whether total emission is reduced. • The development of technologies and various energy structures are considered quantitatively. [ABSTRACT FROM AUTHOR]

Reducing agricultural carbon emissions is an essential lever for mitigating climate change and promoting high-quality agricultural development. Environmental regulation in the form of resource agglomeration, represented by the high-standard farmland construction policy, plays a vital role in the emission reduction process. Using the panel data of 31 provinces in China from 2001 to 2019 and taking the high-standard farmland construction policy as a quasi-natural experiment, this paper constructs a continuous differences-in-differences (DID) model to explore the impact and mechanism of environmental regulation in the form of resource agglomeration (RAER) on agricultural carbon emission reduction. The results show that RAER significantly reduces agricultural carbon emissions by an average of 3.9%. This conclusion still holds after robustness tests such as endogenous tests, eliminating policy interference, and sample reprocessing. This abatement utility is mainly realized through the technique effect of promoting green technology innovation and the composition effect of optimizing crop cultivation structure. Based on the resource attribute characteristics, the agricultural carbon emission reduction effects of RAER are, in descending order, capital and facility. Further study found heterogeneity in four aspects of the effect of RAER on agricultural carbon emission reduction: regional, planted crops, carbon emission sources, and carbon emission intensity. Therefore, decision-makers should deepen environmental regulation reform through resource agglomeration, implement adapting to local conditions for the high-standard farmland construction policy, and promote policy innovation and system optimization of agricultural carbon emission reduction. [ABSTRACT FROM AUTHOR]

The carbon peaking and carbon neutrality strategy have become China's national strategy. Given the significant regional differences in China, the Chinese government has proposed "one policy for one province" guiding principle for carbon emission reduction. This study takes Tianjin as a representative of "a province-level city with high degree of industrialization and prominent emerging industries", and Gansu Province a representative of "a province with a low degree of industrialization but the potential for green energy". Using the integrated modeling frameworkthis study conducts a comparative analysis of the hidden flows generated by inter-provincial inward and outward transfers and extracts a feasible model for carbon neutrality transformation. The study also focuses on carbon emission, GDP changes, carbon hidden flow change in trade and carbon emission reduction path. By comparing the results, this study identifies the mechanism of the industrial spillover effect and carbon emission spillover effect between the two regions. Then it concludes the "cross-regional transfer mode of high-carbon industries" of industrial carbon neutral transformation: more carbon emission allowances are allocated to developing regions represented by Gansu Province, implement regionally differentiated carbon emission reduction constraint policies, and achieve industrial spatial transfer through more inter-provincial transfer. The paper found that in implementing a regionally differentiated carbon emission reduction constraint policy (DE scenario), the transfer of high-carbon industries can achieve the "superposition effect" through inter-provincial transfer. Accordingly, three carbon policy mechanisms for cross-regional transfer of high-carbon industries are summarized. [Display omitted] [ABSTRACT FROM AUTHOR]

Energy Internet (EI) is typically characterized by digitalization and clean energy that seeks to revolutionize the energy system and reduce carbon emissions. Even though several scholars conclude that EI accelerates the clean energy transition of energy system, since the controversial relationship between digitalization and energy consumption in academia, current studies on the carbon emission reduction advantages of the EI are still in dispute. This paper employs the effect of EI's construction on the carbon emission peak goal of China's energy system based on the system dynamics model and different scenarios. The simulation results find that: (1) the construction of the EI could enable China's energy system to meet the carbon reduction commitment in 2028, with a carbon emission peak of 11.61 billion tons; (2) As digitalization and clean energy become more extensively employed, rising energy demand is satisfied by the manner of consuming low-carbon electricity energy. This is thought to be the primary factor that could promote China to achieve the carbon peak goal earlier than expected; (3) The advancement of digitalization has further promoted the decoupling of China's economic growth from carbon emissions. It is projected that China's energy system will still achieve the carbon peak goal by 2030 when the expected annual GDP growth rate is increased to 6.32%, 5.75%, and 4.6% for the years 2020–2025, 2026–2030, and 2031–2035, respectively. These findings might provide a new perspective for quantitative research on the environmental outcomes of the EI and the relationship between environmental improvement and economic growth. [ABSTRACT FROM AUTHOR]

Green finance is essential for supporting the development of green, low-carbon projects and preventing environmental and climate financial risks. Investigating and studying whether and how it can aid in implementing energy transformation is worthwhile. This paper uses 30 provinces from 2004 to 2020 as research samples, the entropy method to construct a green finance measurement system, and the weighted multidimensional vector angle index method to construct an energy low-carbon transformation index based on the actual situation of green finance in China and the existing theoretical research basis. We systematically analyzed each province's spatiotemporal evolution characteristics of green finance and energy structure transformation by constructing a fixed effect model, a GMM model, an intermediary effect model, and a spatial Dubin model. We empirically tested the effect direction, internal mechanism, spatial spillover, and regional heterogeneity of green finance development (GFD) on energy structure transformation (EST) to investigate the low-carbon transformation of energy structures. The findings indicate the following:(1) Green finance plays a positive role in promoting the transformation and development of China's energy structure. (2) The influence of green finance development on the transformation of China's energy structure has significant spatial spillover, exhibiting "local and neighborhood" reciprocity. Through the spatial spillover effect, green finance can encourage the low-carbon transformation of local energy structures and increase the level of low-carbon transformation in neighboring areas. (3) The improvement of the level of green technology innovation and the intensity of environmental regulations are essential channels for green finance to support the low-carbon transformation of the energy structure, and regional heterogeneity will alter this transmission mechanism. The findings of this study provide empirical evidence for the vital role of green finance in achieving the double dividend of economic growth and low-carbon emission reduction. This study provides a new perspective for constructing a green finance system and advancing the dual-carbon objective and a resource for formulating effective regional energy transformation policies. [ABSTRACT FROM AUTHOR]

The increasing methane emissions from the upstream oil and gas sector deviates from the goals of the Paris Agreement on sustainable development and climate control. This paper reviews recent direct measurement results and technological advances in the upstream oil and gas sector, based on more than 100 sources published between 2018 and 2022. No consensus was found on the correlation between methane emissions and well data items such as production volume and well age. Aircraft surveys were the most frequently used technology during the study period. Developed countries lead in direct measurement, with only 12.5% of studies conducted in developing countries. The sensing method and the performance of sensor carriers lead to different characterisations of direct measurement techniques. Growing upstream methane emissions accelerate global warming and pose risks to groundwater. Mitigating super-emitters and reported venting and flares could reduce total methane emissions by 20% and 25%, respectively. China, the world's largest methane emitter, emitted approximately 2135 kt methane from its upstream oil and gas sector, mainly through venting (80%). Direct methane measurements and the strength of government management could assist China in prioritising carbon emission reduction and filling the legislative gap. [Display omitted] [ABSTRACT FROM AUTHOR]

Energy conservation and emission reduction in China's iron and steel industry are crucial for mitigating its environmental pressures. However, uncertainties raise significant management risks when setting energy conservation and emission reduction pathways. Therefore, this paper explores the energy conservation and emission reduction potential in China's iron and steel industry. A 10,000-time Latin hypercube sampling is conducted to simulate the distribution of five types of uncertain factors. In addition, this study uses a Sobol' sensitivity analysis method to recognize the most sensitive factor, and, in specific, analyzes the cost-effectiveness of the technologies via conservation supply curve. The results show that: (1) The uncertainty factors lead to significant fluctuate to the results. In particular, energy conservation will fluctuate by 18.24–40.77%, carbon mitigation by 28.96–55.34%, and SO 2 , NO x and PM mitigation effects will fluctuate by 48.32–79.53%, 22.12–51.77% and 23.92–50.03%, respectively. (2) Structure and equipment parameters are more the most sensitive to energy conservation and carbon mitigation targets, whose Sobol' indices are beyond 0.45. End-of-pipe treatment technologies are more the most sensitive to SO2 and PM reduction targets with Sobol' indices above 0.9. Penetration rates and equipment parameters are more the most sensitive to economic cost targets above 0.8. (3) In 2035, 33 energy conservation technologies and 34 emission reduction technologies will be cost-effective, and they can achieve 69.05–70.14% of energy conservation and 79.03–81.58% of emission reduction potentials, respectively. Based on these findings, this study proposes policy recommendations such as changing the raw material/product structure, upgrading equipment, cooperating actively, and introducing economic incentives and guidelines for technology application. • We establish the energy conservation and emission reduction measure inventory. • Simulation of possible fluctuations due to uncertainties by Latin Hypercube Sampling. • The sensitivity factors are identified through Sobol approach. • Effective management policies need to consider uncertainty factors and sensitivities. [ABSTRACT FROM AUTHOR]

Abstract This paper estimates the shadow price of CO 2 from burning maize straw in the Chinese agricultural sector and explores the related policy implications for decision makers. Using a quadratic directional distance function, we evaluate the production inefficiency and shadow prices of CO 2 reduction for the seven major maize-producing provinces in China for 1996–2014. In general, the efficiency improves over time. Shandong province ranked as the top one with full efficiency considering both economic and environmental impacts as of 2014. The mean shadow price for the CO 2 emission was 0.45 yuan/kg (US$75/t), whereas the province-specific shadow prices varied within the interval bounded by 0 and 0.913 yuan/ha (US$152/t). The marginal abatement cost curve was downward-sloped and indicated the need for curbing CO 2 emission in areas exhibiting the highest pollution rates. Given the marginal abatement cost patterns, the transaction costs associated with implementation of the conservation practices (tillage) should not exceed 335 yuan/ha in order to ensure the welfare gains. This government-provided payment would compensate farmers for yield reductions in favor of implementing conservation practices that would substantially reduce CO 2 emissions. [ABSTRACT FROM AUTHOR]

Abstract Amid the prolific studies on urban metabolism is the relatively sparse research focusing on a specific industrial ecosystem. A general urban metabolism framework disconnected from specific industrial background is at the risk to misunderstand the key drivers of metabolic process, thereby failing to propose applicable measures for improving its sustainability. This paper aims to develop an industrial ecosystem level metabolism framework. This was conducted by following the major analytical tools such as material and energy flow analysis (MEFA) with a focus on the construction ecosystem, which plays a pivotal role in materializing the urban meanwhile generating negative by-products such as greenhouse-gas (GHG), pollutants, and construction waste. The framework was further applied to the construction ecosystem in Shanghai for confirming the major components it includes. Using the data in Shanghai, it was also discovered that the construction industry is generally less efficient in terms of metabolism. It is indicated that population , urbanization rate , concrete input , real estate investment , and the housing demolished and newly built are principal determinants explaining massive construction and demolition (C&D) waste generation in Shanghai. The framework can facilitate the understanding of construction ecosystem metabolic process, investigation of C&D waste generation and its main drivers, and evaluating and improving urban sustainability at an industrial scale. [ABSTRACT FROM AUTHOR]

An ecological footprint (EF) is a vital indicator to measure the sustainable development of a region. Analysis of the driving factors of EFs can facilitate the sustainable development of the population, resources and environment. As the capital city of China, Beijing has a unique municipal economic structure and faces greater urban ecosystem challenges than other cities. This paper used an input-output model to calculate an EF on the basis of the original decomposition analysis model. We consider the population effect, the economic effect, the industrial structure effect, and the footprint intensity to explore the factors driving the changes in the EF of 39 sectors in Beijing. In addition, 9 screened sectors with more significant effects on the change in the EF were analyzed. The results indicated that (1) among the 39 sectors, the crucial factors that drive EF growth are the economic effect, the population effect, and footprint intensity, with contribution rates to total EF of 59.4%, 31.0%, and 7.7%, respectively, while the effect of the industrial structure tends to be 0; and (2) among the 9 screened industries, the population effect and the economic effect promote the growth of the EF of 9 sectors. The reduction in the EF of the primary industry sector is due to the impact of industrial structure effect and footprint intensity. The four effects all promote an increase of the EF of the transportation, warehousing and postal services. These results can be used to propose suggestions for the future development of sectors in Beijing. [ABSTRACT FROM AUTHOR]

China has a high agricultural output and is a significant carbon emitter; thus, reducing carbon emissions in the agricultural sector is crucial for achieving carbon neutrality. To address this, China implemented the National Agricultural Sustainable Development Experimental Demonstration Zone policy in 2018, in which reducing agricultural carbon emissions (ACE) is a subject of concern. We explore the impact of the policy on agricultural carbon emissions reduction (ACER) using the propensity score matching and differences-in-differences (PSM-DID) methods with a series of robustness tests based on the panel data of prefecture-level cities in China from 2011 to 2020. The results indicate that: (1) the policy significantly reduces carbon emissions and impacts carbon emission sources, with the results passing the robustness tests. (2) According to the mechanism test, agricultural financial support mediates carbon emissions reduction, and the policy reduces these emissions by decreasing the intensity of fiscal support. (3) The heterogeneity analysis illustrates that the carbon emissions reduction effect is more evident in cities with a small urban-rural income gap and a high proportion of agricultural output value. Finally, we provide suggestions to reduce carbon emissions from the perspective of national and local governments. This paper is particularly relevant for achieving sustainable agriculture development. [ABSTRACT FROM AUTHOR]

Food production consumes a large amount of water consumption and generates huge amounts of greenhouse gas emissions. Quantitative study of impact food wastage imposing on water and greenhouse gas emissions contributes to public awareness that food wastage will further worsen the resource shortage and climate warming, reducing food wastage accordingly. This paper evaluates the impacts of food wastage in the consumption stage on water resources and the environment in China. The result indicates that in the year 2010, the wastage of major food in China was around 62818 M kg in the consumption link, accounting for 14.5% of the total food production, of which the plant food wastage takes up the majority. The loss of water resources (blue water plus green water) caused by food wastage is 60502 Mm³, more than 10% of the country's total water use. Food wastage has a serious impact on agricultural non-point source pollution and greenhouse gas emissions, resulting in a grey water footprint of 16292 Mm³ and 60.85 M ton of carbon emissions. Taking regional differences of food consumption into consideration, the proportion of water footprints and carbon emissions in the eastern and southern developed areas is relatively higher, while the plant food takes a relatively larger share in water footprints and carbon emissions in the western and central provinces. Reducing food waste is important to remove unnecessary burdens on the environment and natural resources. The optimization of resource utilization in the process of food production is conducive to effectively reduce water footprints and carbon emissions of food; healthy diets shall be popularized among citizens so that the animal food consumption which causes more water footprints and carbon emissions can be decreased, alleviating resource and environmental burdens through reduction of the wastage in food consumption. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2 ) emissions have become a rising concern in China. Few studies have considered spatial correlation and agglomeration effect of CO 2 emissions for adjacent regions and provinces. This paper employs Geographical Weighted Regression (GWR) model to examine the impact of urbanization, industrial structure and energy intensity on CO 2 emissions and reveals the spatial correlation in different provinces in 2005, 2008, 2011 and 2015. The results indicate that there is an obvious spatial effect on CO 2 emissions of each province based on the GWR results. Urbanization is the most significant factor in the increase of CO 2 emissions for all provinces in each year. For the neighboring provinces, a coordinated low-carbon urban construction plan should be carried out based on the urbanization development level. Energy intensity has a positive effect on CO 2 emissions, but the effect on the emission reduction is relatively weak and unstable. It should strengthen exchanges and cooperation between provinces and regions by jointly exploring and promoting technologies to improve the efficiency of resource use and reduce CO 2 emissions. The influence of industrial structure on CO 2 emissions is positive, indicating that the industrial structure adjustment plays an important role in carbon emission reduction. [ABSTRACT FROM AUTHOR]

As a way of disposing municipal solid waste, waste-to-energy not only generates energy but also reduces greenhouse gas emissions. Indeed, waste-to-energy plays a crucial role in addressing various environmental issues such as climate change and security of energy supply. Two waste-to-energy approaches were compared with simple landfill in this study, i.e. incineration with energy recovery (electricity and heat), and landfill with landfill gas utilization. It is imperative to investigate which approach is more effective in terms of GHG emission reduction in the context of different climatic conditions. The effects on GHG emission reductions are examined in the Temperate Dry Zone and Tropical Moist Zone. An assumption is made that in 2020, the waste disposal approach will be switched from simple landfill to waste-to-energy approach in China. The contribution of different waste disposal approach to the GHG reduction (1 t municipal solid waste annually) during 2020–2060 is examined in this paper. Both landfill gas utilization and incineration with energy recovery approaches reduce GHG emissions in all cases compared to the simple landfill. However, this study revealed that landfill gas power generation system is more effective in the Tropical Moist Zone, whereas incineration with energy recovery is a better choice in the Temperate Dry Zone according to the comprehensive benefit. Similarly, the improvement of landfill gas collection rate and the heat recovery efficiency play a crucial role to reduce greenhouse gas emissions during the process of managing the municipal solid waste. [ABSTRACT FROM AUTHOR]

Forecasting CO 2 emissions in China always has been of great significance as it could help the government to improve energy policies and plans. To this end, a novel grey multivariable model is designed in this paper. Compared with the conventional grey multivariable model, which has certain drawbacks of inaccurate prediction and poor adaptability that restrict their applications in practical cases, the proposed model can make three improvements: first, an optimized grey model having a modified background value is proposed to predict the trends of the driving variables. Second, the novel grey multivariable model is established, combined with the changing trends of driving variables. Third, the adjustment coefficient in the new model is optimized to obtain optimal values for the time response function. To demonstrate its efficacy, the proposed model is employed to reproduce and predict the CO 2 emissions from fuel combustion compared with four benchmark models—the results show that the new model yields more accurate forecasting results than the competing models. Eventually, the new model will be used to quantify future Chinese CO 2 emissions from fuel combustion from 2014 to 2020, and the forecasted results can provide a solid basis for formulating environmental policies and energy consumption plans. [ABSTRACT FROM AUTHOR]

This paper uses a panel data of 37 industrial sectors in China from 2003 to 2015, adopts the specification of a fixed effect model, and studies the influence of the coordinated development of inward and outward FDI on industrial pollution emissions. A negative correlation is found between the coordinated development level of inward and outward FDI and the industrial pollution emission level, indicating a pollution emission reduction effect associated with the coordinated development of inward and outward FDI. Furthermore, the moderation effect of global value chain position indicates that an industry can benefit from a stronger emission reduction effect associated with the coordinated development level of inward and outward FDI if it evolves to a higher position in the global value chain. In addition, the heterogeneity analysis indicates that industries with lower energy intensity, a lower ratio of state-owned enterprises, and with more green patents benefit from a more obvious effect on reducing industrial pollution emissions that is caused by the coordinated development of inward and outward FDI. [ABSTRACT FROM AUTHOR]

China has become the largest producer of carbon dioxide (CO 2 ) and non-CO 2 greenhouse gas emissions in the world. However, almost all current Chinese policies are emphasizing the control of CO 2 emissions only, and no goals have been established for non-CO 2 greenhouse gas emission reductions, China risks missing early opportunities for lower-cost abatement of the latter. Aiming to disclose the different effects of CO 2 and non-CO 2 greenhouse gas emissions reductions and provide some suggestions for non-CO 2 greenhouse gas emissions reduction in China, this paper focuses on identifying the price impacts and transmitting paths among different sectors of imposing CO 2 , methane (CH 4 ), nitrous oxide (N 2 O) emission taxes using the Social Accounting Matrix (SAM) model, then further compares the sources of CO 2 and non-CO 2 greenhouse gas emissions based on the big data from the first national census of pollution sources. When the same emission tax is imposed for every ton of CO 2 e, the results clearly show that the prices in all sectors have the greatest increase for CO 2 emissions tax scenario relative to CH 4 and N 2 O emissions tax scenarios. With respect to sectors with larger CH 4 and N 2 O emissions, price change in sectors with larger CO 2 emissions will be responsible for the price change of almost all sectors. Moreover, from the perspective of sources of CO 2 , CH 4 and N 2 O emissions, CO 2 emissions are from almost all industries of the entire economy, and CH 4 and N 2 O emissions are from agriculture, energy mining, and waste. These results indicate that the tax reducing CH 4 and N 2 O emissions will cause lower impacts than the abatement of CO 2 emissions. Integrating the current national policies with the above results, Chinese government should also pay more attention to CH 4 and N 2 O emission reduction. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2) emissions reduction has become a core task with the goal of "emission peak and carbon neutrality", in which green innovation plays an important role. This paper takes the fast-tracking green patent applications (FGPA) system in China as a quasi-natural experiment to empirically study the impact of green innovation incentive-based policies (GIIPs) on CO 2 emissions in Chinese cities by applying a continuous difference-in-difference approach. The results show that the CO 2 emissions of cities in the treatment group are significantly reduced by about 1.6% after the implementation of FGPA relative to that in the control group. After a series of robustness tests, the conclusion is still valid. Furthermore, the significant negative impact on CO 2 emissions is more reflected in cities located in eastern China, cities with lower financial pressure, and cities with more universities. Overall, this study fills up the gap in the empirical research on the impact of FGPA, and casts a new light on the significant environmental performance of GIIPs. The findings obtained through this study are conducive to strengthening and optimizing the implementation of FGPA, and offering policy-makers with a scientific basis of GIIPs to approach the task of reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

Emission trading scheme (ETS) is considered as a tool to reduce emissions at a low cost, which can effectively promote the carbon peak and carbon neutrality. As the main participants in the carbon emission trading (CET) market, the behavior and strategies for governments and different types of enterprises affect the final emission reduction performance. Taking the national carbon market as an example, this paper constructs a tripartite evolutionary game model including governments and power generation enterprises with different emission reduction capacity to analyze the possible game situations in the development process of the CET market. The results show that with the development of the CET market, the governments and power generation enterprises will have different game results. In order to achieve the optimal stable equilibrium and maximize carbon emission reduction, governments should improve regulatory efficiency and formulate appropriate incentive strategies for excess emission reduction and punishment strategies for insufficient emission reduction. In addition, the initial willingness will not affect the final strategy choice of the three parties. Reasonable free carbon quota ratio, lower technology emission reduction cost and higher carbon price can stimulate the enthusiasm of governments and enterprises to reduce emissions. The above results provide a reference for coordinating the relationships between governments and power generation enterprises with different emission reduction capacity in the construction of the CET market in the future. [ABSTRACT FROM AUTHOR]

Recently, comprehensive attention has been attracted to global warming. Meanwhile, China is a country with huge energy consumption and greenhouse gas emission. Therefore, it is urgent for China to reduce the air pollutants embodied in each unit of a good for a less greenhouse gas earth. In this paper, air pollutants embodied in goods consumption as well as import-export trade in China was accounted in 1995–2009. Besides, we checked the structural decomposition analysis of emissions' variation. The results showed: (1) in 1995–2009, air pollutants embodied in goods for consumption and import-export trade in China displayed a rising trend. Emission of carbon dioxide was the largest and methane, carbon monoxide, sulphur oxides, non-methane volatile organic compounds, nitrogen oxides, ammonia, nitrous oxide were in proper sequence based at the average level. (2) Air pollutants embodied in goods exported were larger than those in imported and difference among nations existed. (3) The percentages of carbon dioxide, methane, nitrogen oxides, sulphur oxides, carbon monoxide, non-methane volatile organic compounds embodied in Construction were larger than in other departments on the consumption side, while percentages of carbon dioxide, nitrogen oxides, sulphur oxides, carbon monoxide, non-methane volatile organic compounds embodied in Electrical and Optical Equipment was bigger on the trade side. (4) Emission reduction techniques reduced air pollutants embodied in goods consumption and import and export trade in China. Consequently, China ought to pay attention to emission reduction of carbon dioxide and raise awareness of air pollutants controlling, especially in Construction, Electrical and Optical Equipment and other departments. More importantly, China ought to strengthen cooperation with other nations in emission reduction and developing technologies so as to cut down air pollutants, not only for China but also for the earth. [ABSTRACT FROM AUTHOR]

The Belt and Road Initiative was proposed by China in 2013 to promote the interconnected development and prosperity of all participating countries. In the context of global response to climate change, understanding the embodied carbon transfer change along economic trade before and after the Belt and Road Initiative is essential to reduce carbon overall emission. In this paper, we used a multi-regional input-output model to study the embodied carbon transfer in trade between the Belt and Road countries that have signed cooperation documents with China from 2004 to 2017. The results showed that from 2004 to 2017, the growth rate that China's carbon emissions imported from other Belt and Road Initiative countries was about 1.9 times that of its exports. From 2004 to 2017, the proportion of China's carbon imports from other Belt and Road countries in China's total carbon imports increased from 3.41% to 3.73%, and exports decreased from 6.52% to 6.03%. In both 2004 and 2017, Electricity, Gas and Water sector, Heavy Industry sector, Transport sector were the three largest carbon transfer sectors in China's multilateral trade. In 2017, the embodied carbon transfer by multilateral trade among other Belt and Road countries except China increased by 15.53% compared with 2004. By comparing the characteristics of carbon transfer between China and the Belt and Road countries from 2004 to 2017, this study will provide insights for carbon emission reduction policy setting of Belt and Road Initiative countries. • We took countries that have signed documents with China as research objects. • MRIO model was used to analyze the carbon transfer change from 2004 to 2017. • The embodied carbon transfer in 2017 of BRI increased by 15.53% compared with 2004. • The growth rate of China's carbon imports from BRI was 1.9 times that of exports. [ABSTRACT FROM AUTHOR]

Controlling carbon emissions and sustaining growth constitute essential concerns in the post-financial crisis era combined with low-carbon sustainable development. However, the impact of financial development on carbon emissions remains controversial and lacks mechanisms investigation covering finance spatial attributes. Relying on China province's data during 2005–2019, this paper contributes to the literature by constructing multi-spatial models to investigate how financial geo-density mitigates carbon emission intensity and explore the spatial transmission mechanisms. The results reveal that there is a balance between financial geo-density and carbon emission intensity. The intrinsic mechanisms include: (1) raising financial geo-density is accompanied by the law of marginal diminishing carbon emission intensity tendency; (2) high financial geo-density accelerates technological innovation and industrial structure upgrading, thereby decreasing carbon emission intensity, but drives industrial-scale expansion, thereby increasing carbon emission intensity; and (3) financial institution competition and inter-industry linkage notably influence the relationship between financial geo-density and carbon emission intensity, promoting the emission reduction effect of financial geo-density in accelerating technological innovation and industrial structure upgrading, and suppressing the emission increase effect of financial geo-density in driving industrial expansion. Our findings provide new insights for developing systemic emission reduction policies for employing financial sectors as catch-all and integrating industries and competition. • Mechanism analysis of financial geo-density affects carbon emission intensity (IC). • Propose an integrated spatial model including spatial mediated moderating effects. • Financial geo-density drives IC by industrial-scale expansion. • Reduce IC by technological innovation and industrial upgrading. • Financial institution rivalry and inter-industry link mitigate total driven effect. [ABSTRACT FROM AUTHOR]

Carbon sequestration of blue carbon ecosystems worldwide is as high as 237.6 Tg C/a. China is one of the countries with the most resources of blue carbon, with carbon sequestration of 0.835 Tg C/a. To develop blue economy and facilitate the fulfillment of carbon neutrality, it is of great significance for China to build the blue carbon trading market (BCTM). This paper aimed to improve the participation probability of stakeholders to construct an effective BCTM through evolutionary game theory. First, we constructed a tripartite evolutionary game model including the governments, the suppliers of blue carbon (SBC) and the demanders of blue carbon (DBC), based on the corresponding cost and benefit in BCTM. To further reveal the factors affecting the cooperation of above parties, we analyzed the sensitivity of the stakeholders through five parameters, i.e., proportion of subsidies, unit carbon tax, blue carbon credits, unit price of blue carbon credits, and the cost of carbon emission reduction unit. To verify the game model, a case study of blue carbon credits of mangrove trading was performed. The main conclusions are as follows. In the initial stage of BCTM, the governments need to play a leading role in regulating and incentivizing motivation of the SBC and DBC. Subsidies and carbon taxes are conducive to promoting BCTM to develop into the middle stage. In the middle stage, price and quota of BC credits are two primary parameters to affect the evolutionary results of above three groups. Thus, it's necessary for the governments to adjust these parameters in time. When the trading scale and operation mode of BCTM approaching stable, the market will enter into the mature stage. Then, the governments can reduce subsidies to save fiscal expenditure and lessen the intervention, so as to gradually withdraw from the market. The above conclusions can provide a theoretical basis and reference for the construction of efficient BCTM and promote the integration of blue carbon into the carbon market in China. [Display omitted] [ABSTRACT FROM AUTHOR]

In this paper, we conducted a life cycle assessment (LCA) for the Hydropower-Silicon-Photovoltaic (HSPV) industrial chain in China. The Energy Conservation and Emission Reduction Index in the 13th Five Year Plan of China (ECER-135) is calculated based on the software eBalancev4.7 (eB) and eFootprint (eF). The total environmental impact index of ECER-135 of the HSPV industrial chain is 2.61E-06. The uncertainty result of the comprehensive index is 15.21% and the uncertainty of the inventory data is no more than 30%. The Energy Payback Time (EPBT) of the HSPV industrial chain is calculated as 1.68 years, accounting for only 5.60% of the operating cycle of the PV station. There are 7 impact category indexes of ECER-135, which are Chemical Oxygen Demand (COD), Primary Energy Demand (PED), CO 2 , SO 2 , Ammonia Nitrogen Content (NH 3 –N), NO x and Industrial Water Use (IWU). Considering the contribution of characteristic indexes to ECER-135, the contribution of PED index accounts for 22.93% of ECER-135, which is the major factor to environmental impact, and it is followed by COD, which accounts for 18.40%. Considering the contribution of each stage to ECER-135, PV module manufacturing, BOS manufacturing and SoG-Si manufacturing stages have significantly contributed to ECER-135, in which the PV module manufacturing stage has the greatest contribution to ECER-135, accounting for 97.63%, which is the main stage of impact on the environment. The sensitivity analysis reveals that the highest sensitivity is copper wire consumption, which is 47.83%. It is followed by aluminum consumption during the BOS manufacturing and the PV module manufacturing, which are 41.70% and 29.75% respectively. Finally, compared the total environmental impact of the HSPV industrial chain and the Thermalpower-Silicon-Photovoltaic (TSPV) industrial chain, the results reveal that the HSPV industrial chain has the energy-saving and emission reduction benefits of 2.89E-06, whose comprehensive indexes account for 47.39% of that of the TSPV industrial chain, proving that the HSPV industrial chain has significant energy saving and emission reduction benefits in all indexes. The EPBT of the HSPV industrial chain is only 38.17% of that of the TSPV industrial chain. • Conducting a life cycle assessment of Hydropower-Silicon-Photovoltaic(HSPV). • The contribution, sensitivity and uncertainty analyses of HSPV were conducted. • Serving as to put forward corresponding improvement measures. • The results of Thermalpower-Silicon-Photovoltaic(TSPV) and HSPV were Compared. • The Energy Payback Time of HSPV is only 38.17% of that of TSPV. [ABSTRACT FROM AUTHOR]